trigger

trigger analyzes integrative genomic datasets combining genotypes and traits to map linkages, quantify locus contributions to genome-wide variation, identify eQTL hotspots, and infer gene regulatory relationships.

Key Features:

• Global Linkage Mapping: Performs global linkage mapping correlating genetic markers with gene expression data.
• Multiple-Locus Linkage Analysis: Implements multiple-locus linkage analysis to assess combined genetic influences on gene expression.
• Quantification of GW Variation: Quantifies the proportion of genome-wide (GW) variation explained by individual loci.
• eQTL Hotspot Identification: Detects expression Quantitative Trait Loci (eQTL) hotspots that influence expression across multiple loci.
• Causal Gene Regulatory Probabilities: Estimates pair-wise causal probabilities between genes to infer potential regulatory relationships.
• Gene Regulatory Network Construction: Facilitates construction of gene regulatory networks representing interactions among genes.

Scientific Applications:

• Genomics and molecular biology: Integrates genotype and trait data to investigate gene expression patterns and regulation.
• Genetics: Maps genetic loci underlying complex traits and assesses their contributions to phenotypic variation.
• Systems biology: Supports construction and analysis of gene regulatory networks for studying gene–gene interactions.
• Personalized medicine: Provides locus-level effect estimates and regulatory inference relevant to trait variability in biomedical contexts.

Methodology:

Implemented as an R package within Bioconductor; applies statistical analyses including global and multiple-locus linkage mapping, quantification of genome-wide (GW) variation per locus, eQTL hotspot detection, pair-wise causal probability estimation between genes, and gene regulatory network construction.